Video on demand as a service needs adequate infrastructure (network and servers) to meet Quality of Service (QoS) requirements. Relevant QoS parameters are time to start of the video and sustainable frame rate. Both these parameters are affected when a server that is to stream a video to a client and a network through which the server and the client are connected are loaded. However, the absolute loading of the network is relatively infrequent and it is useful to deploy approaches that exploit the network as a whole thereby overcoming the bottleneck due to relative loading situations. Relative loading indicates that the select paths in the network are overloaded while the rest of the paths are not so loaded. The approaches that exploit the network as a whole offers several advantages including being able to meet QoS requirements under trying conditions, being able to provide a best possible interactive environment for interacting with the video servers, and being able to enhance the return on investment on network and server infrastructure.
A network that supports video streaming can either be a public, general purpose network or a dedicated, special purpose network. Taking into account the cost of providing Video on Demand (VoD) services, it is essential to deploy a suitable mix of public and private networks. The dedicated network is primarily used to address the requirements related to the core activity of the VoD service while the public network is used for meeting the non-core activities of the video-service. A way to effectively meet the core activity of the VoD service is to determine a best possible path for streaming video when the network is loaded. There are several approaches for determining the best possible path and as this path determination is done in real-time, the deployed approach must be quite efficient. Furthermore, the overall approach must be scalable as the resource requirements of a deployed service normally increases with time.
Caching provides an additional way for effectively utilizing the network infrastructure. Caching of the video data helps in reducing the load on the video server as well as on the network. By using the cache effectively along with the point of presence of nodes of the dedicated network, it is possible to offer the video service in a best possible manner.